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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">SSR</journal-id><journal-title-group><journal-title>Scientific and Social Research</journal-title></journal-title-group><issn>2661-4332</issn><eissn>2981-9946</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/ssr.v8i9.15743</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Research Progress on the Application of Digital Technology in Identifying Health Risks for Elderly People in Communities</title><url>https://artdesignp.com/journal/SSR/8/9/10.26689/ssr.v8i9.15743</url><author>LiuQian</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>8</volume><issue>9</issue><history><date date-type="pub"><published-time>2026-10-21</published-time></date></history><abstract>With the acceleration of the aging population process, maintaining the physical function of the elderly and reducing the risk of falls have become important issues in the field of public health. The rapid development of digital technology has provided new technical means for the early identification and dynamic management of the health risks of community-dwelling elderly people. This paper systematically reviews the research progress of digital technologies such as wearable devices, artificial intelligence and machine learning, mobile health applications, virtual reality, and digital twins in the field of identifying health risks for the physical activities of community-dwelling elderly people. It analyzes the current application status, core functions, and main limitations of various technologies, and discusses the key challenges currently faced from aspects such as technology acceptance, data standards, privacy and security, and community adaptability.</abstract><keywords>Digital technology, Elderly people, Physical health risks, Risk identification, Community health management</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] Li RN, Xu CY, Zhang QL, 2025, Research Progress on Elderly Fall Risk Prediction Based on Wearable Sensors. Sensors and Microsystems, 44(10): 7&amp;ndash;11 + 21. https://doi.org/10.13873/J.1000-9787(2025)10-0007-05
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